When performing surgical procedures on the brain, and some other soft organs, it is desirable to remove as much as possible of targeted tissue, such as a tumor or cyst, while preserving as much as possible of surrounding normal tissue. It is also necessary to avoid injury to specific critical structures to avoid inflicting unnecessary impairment on the patient. Typically, both targeted tissue and critical structures are mapped during preoperative magnetic resonance imaging (MRI) and/or computed tomography (CT) scans as part of pre-surgical diagnosis and planning.
When the skull is opened, the brain tends to deform because the brain is very soft, with the skull opened it is no longer confined and can sag under gravity, and because the brain is subjected to alterations in cerebro-spinal fluid (CSF) and blood pressure. The deformation may cause an apparent shift in location of structures mapped during preoperative imaging; this shift may exceed one centimeter. While these structures may be re-located with intra-operative MRI or CT scans, such scans are cumbersome and time consuming to perform and repeated scans may be required as tissue shifts with repositioning of retractors or as portions of tissue are removed. In particular, portions of the brain may sag or shift as other portions of tissue are resected, since resection may alter the fluid plane and the brain may start to sag along the gravitational direction. As a resection cavity goes deeper into the brain, the walls of the cavity may collapse due to gravitation and release of stress in the tissue. The brain deformation due to resection can significantly degrade the accuracy of image guidance. In order to perform the highest quality of neurosurgery within reasonable operative duration, a surgeon must precisely determine intraoperative positions of those targeted tissue and critical structures so that targeted tissue may be removed while preserving nearby or adjacent critical structures.
Similar distortions of tissue shape during surgery may also occur during surgical procedures on other organs as pressures on those organs change from those present during preoperative imaging to those present during surgery.
Electronic stereovision is used for mapping three-dimensional surface structures in a variety of applications. Previously, stereo-optical surface-mapping has been used to map a surface of the brain as deformed after the skull has been opened, a brain deformation model was then used to determine post-opening, and post-tissue-retraction, locations of targeted tissue and critical structures as these locations have shifted from those mapped during preoperative imaging. A PhD thesis describing how a surface map is used with a brain deformation model to determine a tumor shift may be found as Hai Sun, Stereopsis-Guided Brain Shift Compensation, A Thesis, Thayer School of Engineering, Dartmouth College, Hanover, N.H., May 2004, (Hai Sun) the contents of which are incorporated herein by reference.
Hai Sun uses correspondence point triangulation to determine a surface map, and discloses mechanical modeling of an organ, such as the brain, without compensation for additional factors such as surgical cavities in the organ or displacement of tissue by retractors or other surgical instruments. It has been found that the surface map extraction and tumor shift algorithms of Hai Sun fail under some conditions of surface texture. Further, it has been found that there can be significant differences between predicted and actual brain tumor locations if intraoperative surgical cavities and tissue displacement by instruments are not taken into account.
In Simulation of Brain Tumor Resection in Image-guided Neurosurgery Xiaoyao Fan, Songbai Ji, Kathryn Fontaine, Alex Hartov, David Roberts, Keith Paulsen Proc. SPIE 7964, Medical Imaging 2011 (Fan et al. 2011): Visualization, Image-Guided Procedures, and Modeling, 79640U (Mar. 1, 2011); many of the present applicants have discussed an earlier way of determining tumor shift taking into account both intraoperative ultrasound data and stereovision-derived surface map data. The method described in Fan et al, 2011, used a correspondence point method to extract surface maps, then ran a mechanical model with correspondence point displacements at the resection cavity to revise the cavity shape and size, and determine a new, post-resection, mesh model quantity of removed tissue, the new mesh model refined by an iterative process.
Another PhD thesis that discusses use of surface maps obtained with a stereo optical system during neurosurgery is Later Stage Brain Deformation Compensation In Image-Guided Neurosurgery by Xiaoyao Fan, Thayer School of Engineering, Dartmouth College, Hanover, N.H., May 2012, (Fan thesis) the contents of which are incorporated herein by reference. The Fan thesis discusses ways to account for intraoperative surgical cavities and tissue displacement by instruments, thereby providing more accurate predicted intraoperative brain tumor locations.
It is desirable to improve the accuracy and computing speed with which locations of targeted tissue and critical structures are tracked during this deformation, and to more rapidly compute their post-deformation locations.